Frame-to-frame image motion estimation with a fuzzy logic system

Document Type

Conference Proceeding

Publication Date



© 199 IEEE. Fuzzy logic systems show substantial promise for frameto-frame motion estimation. In this paper, a fuzzy logic system with simple rules is shown to provide accurate motion vector estimates with uniform and affine modeled frame-to-frame image motion of real image data. Comparisons are made with Horn and Schunk's optical flow algorithm and Netravali and Robbins' pel recursive algorithm. These comparisons show that the fuzzy logic system presented is superior in the accuracy of its motion vector estimates compared to these two algorithms. These comparisons also show that measures of picture matching such as mean squared error do not necessarily reflect the accuracy of the motion vector estimates found by an algorithm.

Publication Title

Midwest Symposium on Circuits and Systems